Evidence map›Paper›PMID 30355444›Full record

ArticleeLife2018

GABA, not BOLD, reveals dissociable learning-dependent plasticity mechanisms in the human brain.

Polytimi Frangou, Marta Correia, Zoe Kourtzi

Abstract read
In one paragraph

Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Polytimi FrangouDepartment of Psychology, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-3524-0306
Marta CorreiaMRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.ORCID 0000-0002-3231-7040
Zoe KourtziDepartment of Psychology, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-9441-7832

Funding

Alan Turing Institute TU/B/000095Biotechnology and Biological Sciences Research Council BB/P021255/1Medical Research Council MC_U105579212Medical Research Council MC_UU_00005/14Seventh Framework Programme FP7/2007-2013Wellcome 205067/Z/16/ZWellcome Trust 205067/Z/16/Z
6 · The paper itself

Abstract

Experience and training have been shown to facilitate our ability to extract and discriminate meaningful patterns from cluttered environments. Yet, the human brain mechanisms that mediate our ability to learn by suppressing noisy and irrelevant signals remain largely unknown. To test the role of suppression in perceptual learning, we combine fMRI with MR Spectroscopy measurements of GABA, as fMRI alone does not allow us to discern inhibitory vs. excitatory mechanisms. Our results demonstrate that task-dependent GABAergic inhibition relates to functional brain plasticity and behavioral improvement. Specifically, GABAergic inhibition in the occipito-temporal cortex relates to dissociable learning mechanisms: decreased GABA for noise filtering, while increased GABA for feature template retuning. Perturbing cortical excitability during training with tDCs alters performance in a task-specific manner, providing evidence for a direct link between suppression and behavioral improvement. Our findings propose dissociable GABAergic mechanisms that optimize our ability to make perceptual decisions through training.

Indexed as

LearningNeuronal PlasticityAdultFemaleGABAergic Neuronsgamma-Aminobutyric AcidHumansMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMaleNeural InhibitionOccipital LobePerceptionTemporal LobeYoung Adultgamma-Aminobutyric Acidbrain plasticityfunctional MRIhumanmagnetic resonance spectroscopyneurosciencevisual learning

Identifiers

PMID30355444
PMCPMC6202049

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.